Table 3 Vehicle detection results of the VDTC-CEOADL algorithm in ISPRS Potsdam dataset.

From: Optimal deep learning based vehicle detection and classification using chaotic equilibrium optimization algorithm in remote sensing imagery

Class

Accuy

Sensy

Specy

Fscore

AUCscore

Training phase (80%)

 Car

97.21

99.12

83.10

98.43

91.11

 Truck

99.33

71.43

99.77

76.92

85.60

 Van

98.33

89.19

99.15

89.80

94.17

 Pickup car

99.00

54.05

99.94

68.97

77.00

 Average

98.47

78.45

95.49

83.53

86.97

Testing phase (20%)

 Car

98.22

99.02

90.24

99.02

94.63

 Truck

99.55

60.00

100.00

75.00

80.00

 Van

99.11

100.00

99.04

94.29

99.52

 Pickup car

99.55

33.33

100.00

50.00

66.67

 Average

99.11

73.09

97.32

79.58

85.20